U.S. patent application number 17/158056 was filed with the patent office on 2021-07-29 for agent device, agent system, and recording medium.
This patent application is currently assigned to TOYOTA JIDOSHA KABUSHIKI KAISHA. The applicant listed for this patent is TOYOTA JIDOSHA KABUSHIKI KAISHA. Invention is credited to Chikage KUBO, Eiichi MAEDA, Keiko NAKANO, Hiroyuki NISHIZAWA.
Application Number | 20210233528 17/158056 |
Document ID | / |
Family ID | 1000005405413 |
Filed Date | 2021-07-29 |
United States Patent
Application |
20210233528 |
Kind Code |
A1 |
MAEDA; Eiichi ; et
al. |
July 29, 2021 |
AGENT DEVICE, AGENT SYSTEM, AND RECORDING MEDIUM
Abstract
An agent device that receives, from an onboard device installed
in a vehicle, vehicle information relating to the vehicle and
question information corresponding to a question from a user, based
on the vehicle information, confirms a scope of questions for which
generation of a response is not possible, and instructs the onboard
device to block receipt of questions falling within the scope of
questions for which it has been confirmed that response generation
is not possible.
Inventors: |
MAEDA; Eiichi; (Itabashi-ku,
JP) ; KUBO; Chikage; (Chofu-shi, JP) ; NAKANO;
Keiko; (Kawasaki-shi, JP) ; NISHIZAWA; Hiroyuki;
(Itabashi-ku, JP) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
TOYOTA JIDOSHA KABUSHIKI KAISHA |
Toyota-shi |
|
JP |
|
|
Assignee: |
TOYOTA JIDOSHA KABUSHIKI
KAISHA
Toyota-shi
JP
|
Family ID: |
1000005405413 |
Appl. No.: |
17/158056 |
Filed: |
January 26, 2021 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G10L 15/08 20130101;
G10L 15/22 20130101 |
International
Class: |
G10L 15/22 20060101
G10L015/22; G10L 15/08 20060101 G10L015/08 |
Foreign Application Data
Date |
Code |
Application Number |
Jan 29, 2020 |
JP |
2020-013028 |
Claims
1. An agent device comprising: a memory; and a processor coupled to
the memory, the processor being configured to: receive, from an
onboard device installed in a vehicle, vehicle information relating
to the vehicle and question information corresponding to a question
from a user, based on the vehicle information, confirm a scope of
questions for which generation of a response is not possible, and
instruct the onboard device to block receipt of questions falling
within the scope of questions for which it has been confirmed that
response generation is not possible.
2. The agent device of claim 1, wherein the processor is configured
to search a database storing state information indicating
correspondence, to respective vehicles, of manuals storing
responses, and to confirm the scope of questions for which response
generation is not possible based on presence or absence of a manual
corresponding to the vehicle information.
3. The agent device of claim 1, wherein the processor is configured
to confirm the scope of questions for which response generation is
not possible at a time of start-up of the vehicle.
4. An agent system comprising: an agent device that includes a
memory and a processor coupled to the memory, the processor being
configured to: receive, from an onboard device installed in a
vehicle, vehicle information relating to the vehicle and question
information corresponding to a question from a user, based on the
vehicle information, confirm a scope of questions for which
generation of a response is not possible, and instruct the onboard
device to block receipt of questions falling within the scope of
questions for which it has been confirmed that response generation
is not possible; and the onboard device, which is configured to
control a display device provided to the vehicle so as to gray out
an input button relating to the question when instructed by the
agent device to block receipt.
5. A non-transitory recording medium storing a program that is
executable by a computer to perform processing, the processing
comprising: receiving, from an onboard device installed in a
vehicle, vehicle information relating to the vehicle on at a time
of start-up of the vehicle, and receiving question information
corresponding to a question from a user, based on the vehicle
information, confirming a scope of questions for which generation
of a response is not possible; and instructing the onboard device
to block receipt of questions falling within the scope of questions
for which it has been confirmed that response generation is not
possible.
6. The non-transitory recording medium of claim 5, wherein the
processing further comprises searching a database storing state
information indicating correspondence, to respective vehicles, of
manuals storing responses, and confirming the scope of questions
for which response generation is not possible based on presence or
absence of a manual corresponding to the vehicle information.
7. The non-transitory recording medium of claim 5, wherein the
processing further comprises confirming the scope of questions for
which response generation is not possible at a time of start-up of
the vehicle.
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application is based on and claims priority under 35
USC 119 from Japanese Patent Application No. 2020-013028 filed on
Jan. 29, 2020, the disclosure of which is incorporated by reference
herein.
BACKGROUND
Technical Field
[0002] The present disclosure relates to an agent device, an agent
system, and a recording medium recording a program therein used to
provide a response to a question asked by a user.
Related Art
[0003] Japanese Patent Application Laid-Open (JP-A) No. 2001-141500
discloses a vehicle agent processing device that provides
information relevant to the operation of various onboard units.
[0004] Suppose that the agent processing device of JP-A No.
2001-141500 were to be applied to an agent used to search an
owner's manual. In such cases, were a question from a user to be
received when the agent is unable to provide support for some or
all functionality of a vehicle, for example in cases in which an
owner's manual stored with responses to questions has not been
compiled, or cases in which an owner's manual is temporarily
unavailable due to an ongoing update, a response such as "unknown"
or "not found" may be given to the question, causing frustration
for the user.
SUMMARY
[0005] An aspect of the disclosure is an agent device that
includes: a memory; and a processor coupled to the memory. The
processor is configured to: receive, from an onboard device
installed in a vehicle, vehicle information relating to the vehicle
and question information corresponding to a question from a user,
based on the vehicle information, confirm a scope of questions for
which generation of a response is not possible, and instruct the
onboard device to block receipt of questions falling within the
scope of questions for which it has been confirmed that response
generation is not possible.
BRIEF DESCRIPTION I/F THE DRAWINGS
[0006] Exemplary embodiments of the present disclosure will be
described in detail based on the following figures, wherein:
[0007] FIG. 1 is a diagram illustrating an example of schematic
configuration of a manual provision system according to a first
exemplary embodiment;
[0008] FIG. 2 is a block diagram illustrating an example of
hardware configuration of a vehicle of the first exemplary
embodiment;
[0009] FIG. 3 is a block diagram illustrating an example of
hardware configuration of a server of the first exemplary
embodiment;
[0010] FIG. 4 is a block diagram illustrating an example of
functional configuration of an agent server of the first exemplary
embodiment;
[0011] FIG. 5 is a block diagram to explain functionality of a
manual provision system of the first exemplary embodiment;
[0012] FIG. 6 is a diagram illustrating an example of a training
data generation method;
[0013] FIG. 7 is a sequence chart illustrating an example of a flow
of processing relating to confirmation of an agent association
status and processing to reflect the association status on a
monitor in a manual provision system of the first exemplary
embodiment;
[0014] FIG. 8 illustrates an example of display on a monitor in a
case in which agent association exists;
[0015] FIG. 9 is illustrates an example of display on a monitor in
a case in which agent association does not exist;
[0016] FIG. 10 is a sequence chart illustrating an example of a
flow of processing to infer the intent of a question in a manual
provision system of the first exemplary embodiment;
[0017] FIG. 11 is a sequence chart (continued from FIG. 10)
illustrating an example of a flow of processing to infer the intent
of a question in a manual provision system of the first exemplary
embodiment;
[0018] FIG. 12 is a diagram illustrating an example of information
relating to response information presented to an occupant;
[0019] FIG. 13 is a sequence chart illustrating an example of a
flow of processing to infer the intent of a question in a manual
provision system of a second exemplary embodiment;
[0020] FIG. 14 is a sequence chart (continued from FIG. 13)
illustrating an example of a flow of processing to infer the intent
of a question in a manual provision system of the second exemplary
embodiment; and
[0021] FIG. 15 is a block diagram illustrating an example of
functional configurations of an agent server of a third exemplary
embodiment.
DETAILED DESCRIPTION
First Exemplary Embodiment
[0022] As illustrated in FIG. 1, a manual provision system 10
configuring an agent system of a first exemplary embodiment
includes plural vehicles 12 and plural servers 30. An onboard
device 20 serving as a notification device is installed in each of
the vehicles 12. The servers 30 include a human machine interface
(hereafter "HMI") server 14 serving as an interface device with an
HMI function, an agent server 16 serving as an agent device, an
owner's manual (hereafter also abbreviated to OM) server 18, and a
data server 19.
[0023] The onboard devices 20 of the respective vehicles 12, the
HMI server 14, the OM server 18, and the data server 19 are
connected together through a network N1. The HMI server 14 and the
agent server 16 are connected together through a network N2. Note
that the agent server 16 may also be connected to the network N1,
similarly to the other servers 30.
[0024] Vehicle
[0025] As illustrated in FIG. 2, each of the vehicles 12 according
to the present exemplary embodiment includes the onboard device 20,
plural ECUs 22, a microphone 24 serving as an audio input device,
an input switch 26 serving as an operation input device, a monitor
28 serving as a display device, and a speaker 29.
[0026] The onboard device 20 includes a central processing unit
(CPU) 20A, read only memory (ROM) 20B, random access memory (RAM)
20C, an in-vehicle communication interface (I/F) 20D, a wireless
communication I/F 20E, and an input/output I/F 20F. The CPU 20A,
the ROM 20B, the RAM 20C, the in-vehicle communication I/F 20D, the
wireless communication I/F 20E, and the input/output I/F 20F are
connected together through an internal bus 20G so as to be capable
of communicating with each other.
[0027] The CPU 20A is a central processing unit that executes
various programs and controls various sections. Namely, the CPU 20A
reads a program from the ROM 20B, and executes the program using
the RAM 20C as a workspace.
[0028] The ROM 20B stores various programs and various data. The
ROM 20B of the present exemplary embodiment is stored with a
control program used to control the onboard device 20.
[0029] The RAM 20C serves as a workspace that temporarily stores
programs and data.
[0030] The in-vehicle communication I/F 20D is an interface for
connecting to the ECUs 22. This interface employs a CAN
communication protocol. The in-vehicle communication I/F 20D is
connected to an external bus 20H serving as a communication path.
The ECUs 22 serve as control devices, and plural thereof are
provided corresponding to respective functionality of the vehicle
12. Examples of the ECUs 22 of the present exemplary embodiment
include a vehicle control ECU, an engine ECU, a brake ECU, a body
ECU, a camera ECU, and a multimedia ECU.
[0031] The wireless communication I/F 20E is a wireless
communication module used to communicate with the servers 30. The
wireless communication module employs a communication protocol such
as 5G; LTE, or Wi-Fi (registered trademark). The wireless
communication I/F 20E is connected to the network N1.
[0032] The input/output I/F 20F is an interface used to communicate
with the microphone 24, the input switch 26, the monitor 28, and
the speaker 29 installed in the vehicle 12.
[0033] The microphone 24 is provided in a front pillar, dashboard,
or the like of the vehicle 12, and is a device that picks up sound
emanating from a user, namely an occupant of the vehicle 12.
[0034] The input switch 26 is provided to an instrument panel, a
center console, a steering wheel, or the like, and is a switch
configured for input operation by a finger of the occupant. For
example, a push button ten-key pad or a touch pad may be employed
as the input switch 26.
[0035] The monitor 28 is provided to the instrument panel, a meter
panel, or the like, and is a liquid crystal monitor used to display
images relating to an owner's manual and response information,
described later. The monitor 28 may be provided in the form of a
touch panel that doubles as the input switch 26.
[0036] The speaker 29 is provided in the instrument panel, center
console, front pillar, dashboard, or the like, and is a device used
to output audio relating to response information.
[0037] Servers
[0038] As illustrated in FIG. 3, each of the servers 30 includes a
CPU 30A, this being an example of a hardware processor, ROM 30B
corresponding to memory, RAM 30C, storage 30D, and a communication
I/F 30E. The CPU 30A, the ROM 30B, the RAM 30C, the storage 30D,
and the communication I/F 30E are connected together through an
internal bus 30G so as to be capable of communicating with each
other. The CPU 30A, the ROM 30B, the RAM 30C, and the communication
I/F 30E have functionality equivalent to that of the CPU 20A, the
ROM 20B, the RAM 20C, and the wireless communication I/F 20E of the
onboard device 20 described above.
[0039] The storage 30D includes a hard disk drive (HDD) or a solid
state drive (SSD), and is stored with various programs and various
data.
[0040] The CPU 30A functions as an OMA interaction control section
36, namely a reception section 50, an acquisition section 52, a
confirmation section 53, an instruction section 54, a provision
section 56, and as an intent inference section 38, by loading a
program from the storage 30D and executing this program using the
RAM 30C as a workspace.
[0041] A processing program 100 and a data group 110 are stored in
the storage 30D of the present exemplary embodiment. The processing
program 100 is a program for implementing the various functionality
included in the server 30.
[0042] HMI Server
[0043] The HMI server 14 includes functionality to receive
questions from the onboard device 20, and to refer to the agent
server 16 for a response to a question relating to an owner's
manual.
[0044] As illustrated in FIG. 5, the CPU 30A of the HMI server 14
of the present exemplary embodiment executes the processing program
100 so as to function as an HMI interaction control section 32,
serving as a selection section.
[0045] The HMI interaction control section 32 communicates with the
onboard device 20. The HMI interaction control section 32 acquires
audio information from the occupant of the vehicle 12 transmitted
from the onboard device 20, performs speech recognition, and
converts the audio information to text information. Note that in
the present exemplary embodiment, it is anticipated that questions
are asked in the form of utterances from the occupant of the
vehicle 12. Accordingly, audio information relating to an occupant
utterance serves as input information input to the onboard device
20 by the occupant. Input information is configured by audio
information relating to a question uttered by the occupant, for
example "How do I turn off this lamp?" or "What is the switch with
an A in a circle?".
[0046] The HMI interaction control section 32 also interprets the
intent of the occupant utterance based on the converted text
information. In cases in which the HMI interaction control section
32 interprets that the occupant has asked a question relating to
the owner's manual, the HMI interaction control section 32 refers
to the agent server 16 regarding this question. The HMI interaction
control section 32 also transmits text information relating to this
question to the agent server 16, and receives response information
relating to the response from the agent server 16.
[0047] The HMI interaction control section 32 also transmits the
response information received from the agent server 16 to the
onboard device 20. Note that the response information includes both
text information and audio information relating to a response to
the question. The text information includes a URL used to view HTML
data from the owner's manual.
[0048] The HMI server 14 also includes functionality to confirm an
association status of an agent (owner's manual agent; hereafter
OMA) handling the question relating to the owner's manual, based on
vehicle information acquired from the onboard device 20. This
functionality will be described in detail later.
[0049] Agent Server
[0050] The agent server 16 functions as an OMA. The agent server 16
acquires vehicle information for the corresponding vehicle 12 and
text information relating to the question from the HMI server 14,
and also acquires CAN information, this being state information
relating to a state of the vehicle 12, from the data server 19. The
agent server 16 also provides the HMI server 14 with response
information relating to the response to the question.
[0051] In the agent server 16 of the present exemplary embodiment,
the CPU 30A executes the processing program 100 so as to function
as the OMA interaction control section 36 and the intent inference
section 38 illustrated in FIG. 4. The OMA interaction control
section 36 includes the reception section 50, the acquisition
section 52, the confirmation section 53, the instruction section
54, and the provision section 56.
[0052] The data group 110 of the agent server 16 includes
vehicle-to-OM association data 200, intent inference ID management
data 210, QA data 220, word normalization data 230, and trained
models 240, as illustrated in FIG. 5.
[0053] The vehicle-to-OM association data 200 is data in which
vehicle information relating to the vehicle identification number,
vehicle type, grade, equipment and so on of each of the vehicles 12
is stored in association with OM item codes allocated to respective
owner's manuals. The vehicle-to-OM association data 200 is an
example of a database storing association statuses of manuals
stored with question responses to respective vehicles.
[0054] The intent inference ID management data 210 is data in which
association relationships between the OM item codes and intent
inference engines are stored. In the intent inference ID management
data 210, intent inference engine IDs are stored in association
with the respective OM item codes. The intent inference engine IDs
are IDs allocated to respective intent inference engines used
during the execution of intent inference processing, described
later. Individual intent inference engines are provided for similar
or related owner's manuals.
[0055] The QA data 220 is data in which response information is
held linked to intent labels allocated to each response. Note that
the intent labels are label numbers provided as a result of
inferring intent from content uttered by an occupant. The response
information relates to responses to questions, and includes text
for display, images for display, text for text-to-speech readout,
information regarding URLs to display owner's manuals, and so
on.
[0056] The word normalization data 230 is data employed to
normalize words, and is used in a pre-processing stage before
intent inference processing. This pre-processing refers to
processing to standardize differences in notation and phrasing. For
example, the word normalization data 230 may include data for
standardizing differences in notation, such as information
indicating that "off" and "OFF" correspond to the same word. As
another example, the word normalization data 230 may include data
for standardizing differences in phrasing, such as information
indicating that "tire pressure warning lamp" and "air pressure
warning lamp" refer to the same thing.
[0057] The trained model 240 is data generated by performing
machine learning employing training data based on past states of
the vehicle 12 prior to a reception timing when the reception
section 50, described later, received text information, and on past
occupant questions. The input of the training data is CAN
information relating to past states of the vehicle 12, and text
information relating to plural expressions relevant to questions
during these past states, and an intent label relating to a correct
response to this question is the output. The CAN information
relating to past states is an example of past state information.
One of the trained models 240 is trained in advance for each intent
inference engine.
[0058] FIG. 6 illustrates an example of training data based on past
questions and past CAN information. As illustrated in FIG. 6, the
onboard device 20 stores CAN information-based illumination states
of warning lamps and display lamps and notification states of
notification sounds for the corresponding vehicle 12. The onboard
device 20 also stores audio input to the microphone 24.
[0059] Note that when the onboard device 20 receives an occupant
utterance, the onboard device 20 also acquires active illumination
state and notification state items from the CAN information for a
determination period running from a timing A that is a
predetermined duration prior to a reception timing B, up to the
timing B. In the example in FIG. 6, during the predetermined
duration from the timing A to the timing B, a display 1, a display
2, and a notification sound 1 are ON, in other words are active.
The training data generates input data in which a feature amount of
"1" is applied to any element that is active for a predetermined
duration or longer during the determination period.
[0060] The uttered question is converted to text by speech
recognition, and words are extracted therefrom. Extracted candidate
words correspond to "expressions". In the example of FIG. 6, since
a word 2 is included in the utterance, the feature amount of "1" is
applied to the word 2 in the generated input data.
[0061] As output, intent labels associated with the intent of the
utterance are applied to the input applied with feature amounts as
described above. In the example of FIG. 6, a No. 1 intent label is
associated with the input. In the above-described example of the
present exemplary embodiment, in a case in which a question
including the word 2 is asked when the display 1, the display 2,
and the notification sound 1 are in active states, machine learning
is performed using training data so as to generate the No. 1 intent
label in response to this question.
[0062] In the OMA interaction control section 36 illustrated in
FIG. 5, firstly the reception section 50 receives text information
configuring question information, and also receives vehicle
information. The reception section 50 is also capable of receiving
the CAN information relating to the state of the vehicle 12. Next,
in cases in which the text information corresponds to a question
from the occupant, the acquisition section 52 of the OMA
interaction control section 36 acquires a response to the question
based on the vehicle information, the CAN information, and the text
information. The acquired response is obtained by performing intent
inference processing to infer the intent of the question.
[0063] More specifically, the acquisition section 52 consults the
vehicle-to-OM association data 200 to acquire the OM item code
associated with a given vehicle 12 based on the vehicle information
for this vehicle 12. In cases in which the acquisition section 52
is unable to acquire an OM item code, the acquisition section 52
notifies the HMI interaction control section 32 that "this service
is unavailable". The acquisition section 52 also consults the
intent inference ID management data 210 to acquire the OMA intent
inference engine ID applicable to the given vehicle 12 based on the
acquired OM item code.
[0064] The acquisition section 52 then refers to the intent
inference section 38 using input values of the text information
relating to the question, the CAN information of the vehicle 12,
and the OMA intent inference engine ID, and acquires an intent
label corresponding to a response. In cases in which no intent
label could be acquired, the provision section 56 transmits
no-results information indicating that no results were found to the
HMI server 14. On the other hand, in cases in which a single intent
label has been acquired, the acquisition section 52 consults the QA
data 220 to acquire the associated response information based on
the acquired intent label and the OM item code.
[0065] Note that in cases in which plural intent labels are
acquired, the acquisition section 52 may consult the QA data 220 to
generate option information relating to plural response options. In
cases in which option information is generated, this option
information is transmitted to the onboard device 20, and result
information, this being a result selected by the occupant, can be
acquired from the onboard device 20 in order to identify a single
intent label.
[0066] The confirmation section 53 of the OMA interaction control
section 36 includes functionality to confirm an association status
of the vehicle 12 to the OMA. As the OMA association status,
confirmation may be made not only as to whether or not generation
of a response to any occupant question is possible, but also as to
whether or not generation of a response to certain questions is
possible. The confirmation section 53 searches the vehicle-to-OM
association data 200 and confirms the OMA association status based
on the presence or absence of an OM item code associated with the
vehicle information received by the reception section 50.
[0067] The instruction section 54 of the OMA interaction control
section 36 instructs the onboard device 20 such that the onboard
device 20 blocks receipt of questions falling within a scope for
which the confirmation section 53 has confirmed that response
generation is not possible. The functionality of the instruction
section 54 will be described in detail later.
[0068] The provision section 56 of the OMA interaction control
section 36 transmits one out of no-results information, response
information, or option information to the HMI interaction control
section 32 of the HMI server 14. More specifically, in cases in
which the acquisition section 52 has been unable to acquire an
intent label, the acquisition section 52 transmits no-results
information to the HMI server 14. In cases in which the acquisition
section 52 has acquired a single intent label, the acquisition
section 52 transmits the associated response information to the HMI
server 14. In cases in which the acquisition section 52 has
acquired plural intent labels, the acquisition section 52 transmits
the generated option information to the HMI server 14.
[0069] The intent inference section 38, serving as an inference
section, executes intent inference processing as inference
processing to infer the intent of a question from an occupant. The
intent inference processing is executed employing the intent
inference engine associated with the intent inference engine ID.
Specific explanation follows regarding execution of the intent
inference processing. Firstly, the intent inference section 38 uses
the word normalization data 230 to perform pre-processing on the
text of the acquired text information. The pre-processing
standardizes differences in notation and differences in phrasing.
Next, the intent inference section 38 inputs the trained model 240
prepared for the corresponding intent inference engine with the
pre-processed text information and the CAN information of the
vehicle 12, and outputs an intent label and confidence score. The
confidence score corresponds to a probability that the text
information input to the trained model 240 matches the inferred
intent label. The intent inference section 38 then provides any
intent labels having a confidence score exceeding a predetermined
value, namely intent labels vouched to have at least a
predetermined probability of dependability, to the OMA interaction
control section 36.
[0070] OM Server
[0071] The OM server 18 is a server 30 that provides an owner's
manual. The data group 110 of the OM server 18 includes OM data
300, this being HTML data relating to owner's manuals. In a case in
which an image relating to response information is displayed on the
monitor 28 of the vehicle 12, the occupant selects a URL included
in the image to execute a transmission request for HTML data
associated with the URL to the OM server 18. The HTML data of the
owner's manual associated with the URL is thus transmitted to the
onboard device 20 to be displayed on the monitor 28.
[0072] Data Server
[0073] The data server 19 is a server 30 that acquires CAN
information from the onboard device 20, and provides CAN
information to the agent server 16. The CPU 30A of the data server
19 of the present exemplary embodiment executes the processing
program 100 so as to function as a data management section 39.
[0074] The data group 110 of the data server 19 includes a CAN
database 400 configured of data including vehicle information of
the respective vehicles 12 and CAN information associated with the
vehicle information. The data management section 39 acquires the
CAN information for the respective vehicles 12 from the onboard
devices 20 at predetermined intervals, and stores this in the CAN
database 400. The data management section 39 also provides CAN
information to the agent server 16 when requested to do so by the
agent server 16.
[0075] Note that by acquiring CAN information and audio information
relating to questions from the onboard devices 20, the data
management section 39 of the data server 19 is able to generate
training data to generate new trained models 240 by performing
machine learning. The new trained models 240 thus generated are
transmitted to the agent server 16 as updates.
[0076] Control Flow
[0077] (1) Processing Relating to Agent Association Status
Confirmation and Processing to Reflect Association Status on
Monitor
[0078] Explanation follows regarding processing performed for the
respective vehicles 12, including processing relating to OMA
association status confirmation and processing to reflect this
association status on the monitor 28, with reference to the
sequence chart of FIG. 7.
[0079] Firstly, explanation follows regarding processing to confirm
the OMA association status.
[0080] At step S10 in FIG. 7, the onboard device 20 detects
start-up of the corresponding vehicle 12. Start-up here refers to a
state in which an accessory switch (ACC) has been turned ON.
[0081] At step S11, the onboard device 20 transmits vehicle
information of the vehicle 12 to the HMI server 14.
[0082] At step S12, the HMI interaction control section 32 of the
HMI server 14 orders confirmation of the OMA association status.
Namely, the HMI interaction control section 32 sends a confirmation
request to the agent server 16.
[0083] At step S13, the HMI interaction control section 32
transmits vehicle information to the OMA interaction control
section 36 of the agent server 16.
[0084] At step S14, the OMA interaction control section 36 searches
the OM item codes. More specifically, the OMA interaction control
section 36 consults the vehicle-to-OM association data 200 to
search for whether or not an OM item code associated with the
acquired vehicle information is present.
[0085] At step S15, the OMA interaction control section 36 confirms
whether or not an OMA association exists. More specifically, in
cases in which the OMA interaction control section 36 is able to
find an OM item code associated with the vehicle information, the
OMA interaction control section 36 confirms that an association
exists, and in cases in which the OMA interaction control section
36 is unable to find an OM item code associated with the vehicle
information, the OMA interaction control section 36 confirms that
an association does not exist.
[0086] At step S16, the OMA interaction control section 36 notifies
the onboard device 20 of the association status via the HMI server
14.
[0087] At step S17, the onboard device 20 updates the presence or
absence of OMA association.
[0088] Next, explanation follows regarding processing to reflect
the OMA association status on the monitor 28.
[0089] At step S20 in FIG. 7, the onboard device 20 receives an
utterance. For example, suppose the occupant of the vehicle 12 says
"My agent", this being a keyword used to start up the agent, into
the microphone 24.
[0090] When this is performed, at step S21, the onboard device 20
displays an initial screen relating to agent functionality on the
monitor 28. FIG. 8 and FIG. 9 are examples of the initial screen
displayed on the monitor 28. Plural input buttons 80 relating to
functionality of the onboard device 20 are displayed on the monitor
28. The input buttons 80 include a navigation button 80A, an audio
button 80B, a phone call button 80C, a vehicle function button 80D,
and a help button 80E. In the present exemplary embodiment, the
help button 80E is associated with an OMA.
[0091] When the initial screen is displayed on the monitor 28, in
cases in which OMA association exists, as illustrated in FIG. 8 the
help button 80E is displayed as active and is selectable. On the
other hand, when the initial screen is displayed on the monitor 28,
in cases in which OMA association does not exist, as illustrated in
FIG. 9 the help button 80E display is grayed out and is not
selectable. In such cases, the onboard device 20 is unable to
receive questions relating to functionality of the vehicle 12 when
the display has been grayed out.
[0092] (2) Processing to Present Response to Question
[0093] Explanation follows regarding processing performed when the
occupant of the vehicle 12 has asked a question, up to and
including presentation of a response, with reference to the
sequence charts of FIG. 10 and FIG. 11.
[0094] At step S30 in FIG. 10, the onboard device 20 acquires CAN
information through the external bus 20H.
[0095] At step S31, the onboard device 20 transmits the acquired
CAN information to the data server 19 together with vehicle
information of the vehicle 12. Note that although in the present
exemplary embodiment the vehicle information and the CAN
information are transmitted from the onboard device 20 to the data
server 19 at predetermined intervals, there is no limitation
thereto, and transmission from the onboard device 20 to the data
server 19 may be performed whenever the CAN information
changes.
[0096] At step S32, the data server 19 stores the information
acquired by the data management section 39 in the CAN database 400.
The stored information includes vehicle information, CAN
information, and a reception timestamp.
[0097] At step S40, the onboard device 20 receives an utterance
from the occupant. More specifically, the CPU 20A of the onboard
device 20 acquires audio uttered into the microphone 24 by the
occupant as audio information. For example, suppose that the
occupant utters the phrase "A meter lamp has come on, but what does
it mean?" in a state in which a tire pressure warning lamp of the
vehicle 12 has lit up. When this is performed, the utterance is
received such that the utterance of "A meter lamp has come on, but
what does it mean" is acquired as audio information.
[0098] At step S41, the onboard device 20 transmits the acquired
audio information to the HMI server 14 together with vehicle
information of the vehicle 12 and an utterance start timestamp.
[0099] At step S42, the HMI interaction control section 32 of the
HMI server 14 performs speech recognition. The audio information is
thus converted into text information. Note that when this speech
recognition is performed, the audio information is determined to be
a question in cases in which a linguistic feature corresponding to
a question is included in the text information.
[0100] At step S43, the HMI interaction control section 32
transmits the vehicle information, the utterance start timestamp,
and the text information to the OMA interaction control section 36
of the agent server 16. In the above example, the text string "A
meter lamp has come on, but what does it mean" that has been
determined to be a question is transmitted as the text
information.
[0101] At step S44, the OMA interaction control section 36 searches
for CAN information. Namely, the OMA interaction control section 36
attempts to acquire CAN information from the data server 19.
[0102] At step S45, the OMA interaction control section 36
transmits the vehicle information and the utterance start timestamp
to the data server 19.
[0103] At step S46, the data management section 39 of the data
server 19 transmits CAN information or no-information notification
to the agent server 16. The transmitted CAN information is acquired
by the data management section 39 referring to the CAN database 400
and searching for CAN information relating to the vehicle
information of the vehicle 12 and also relating to a reception
timestamp just before the utterance start timestamp. Note that the
no-information notification is notification to indicate that there
is no CAN information in cases in which CAN information associated
with the vehicle information and the utterance start timestamp
could not be acquired.
[0104] At step S47, the OMA interaction control section 36
identifies an associated OM item code based on the vehicle
information. Namely, the OMA interaction control section 36
identifies an owner's manual associated with the vehicle
identification number, vehicle type, grade, equipment, or the like
of the vehicle 12. Note that the CAN information may also be
employed to identify the OM item code. In such cases, if the OMA
interaction control section 36 is unable to acquire the newest CAN
information of the vehicle 12 as a result of poor communication or
the like, the OM item code considered standard for the vehicle type
or grade may be identified.
[0105] At step S48, the OMA interaction control section 36
identifies the associated intent inference engine ID based on the
OM item code. Namely, the intent inference engine associated with
the owner's manual of the vehicle 12 is identified. Note that CAN
information may also be employed to identify the intent inference
engine ID. In such cases, if the OMA interaction control section 36
is unable to acquire the newest CAN information of the vehicle 12
as a result of poor communication or the like, the intent inference
engine ID considered standard for the vehicle type or grade may be
identified.
[0106] At step S49, the OMA interaction control section 36 provides
the text information acquired from the HMI server 14, the CAN
information acquired from the data server 19, and the intent
inference engine ID to the intent inference section 38.
[0107] At step S50, the intent inference section 38 executes intent
inference processing. The intent inference section 38 thus outputs
intent labels associated with the text information and the CAN
information. In the example of the present exemplary embodiment,
intent labels associated with the intent inferred from the text
information of "A meter lamp has come on, but what does it mean"
are output.
[0108] Moving on to FIG. 11, at step S51, the intent inference
section 38 provides the OMA interaction control section 36 with the
single intent label with the highest confidence score. Note that in
cases in which an intent label with a confidence score exceeding
the predetermined value is not output, the intent inference section
38 provides the OMA interaction control section 36 with no-label
information to indicate that no intent label has been returned.
[0109] At step S52, the OMA interaction control section 36
generates response information based on the intent label. Namely,
the OMA interaction control section 36 consults the QA data 220 to
generate response information configured by a combination of text
for display, images for display, text for text-to-speech readout, a
URL to display the owner's manual, and the like.
[0110] At step S53, the OMA interaction control section 36
transmits the response information to the HMI server 14.
[0111] At step S54, the HMI interaction control section 32
generates presentation information. The presentation information is
information for transmission to the onboard device 20, and is
response information from which information that does not need to
be presented using the monitor 28 or the speaker 29, for example
the intent label, the OM item code, and the like, has been cut.
Note that the response information may also be employed as-is as
the presentation information.
[0112] At step S55, the HMI interaction control section 32
transmits the presentation information to the onboard device
20.
[0113] At step S56, the onboard device 20 presents the received
presentation information to the occupant of the vehicle 12. More
specifically, the CPU 20A of the onboard device 20 displays images
relating to the received presentation information on the monitor
28, and outputs audio relating to the received presentation
information from the speaker 29. For example, as illustrated in
FIG. 12, the CPU 20A di splays an explanation regarding the tire
pressure warning system on the monitor 28, and outputs "That is a
warning from the tire pressure warning system" as audio from the
speaker 29.
[0114] Summary of First Exemplary Embodiment
[0115] The manual provision system 10 of the present exemplary
embodiment is capable of providing a response to the onboard device
20 obtained by inferring the intent of the question when the
occupant of the vehicle 12 asks a question which is input via the
onboard device 20.
[0116] In the agent server 16 of the present exemplary embodiment,
the reception section 50 that receives text information receives
vehicle information when the vehicle 12 is started up. Based on the
vehicle information, the confirmation section 53 confirms a scope
of questions for which response generation is not possible. Note
that cases in which "response generation is not possible" include
cases in which an owner's manual stored with responses to questions
has not been compiled, and cases in which an owner's manual is
temporarily unavailable due to an ongoing update. The instruction
section 54 instructs the onboard device 20 such that the onboard
device 20 blocks receipt of questions falling within the scope for
which the confirmation section 53 has confirmed that response
generation is not possible. Accordingly, the present exemplary
embodiment is capable of suppressing a sense of frustration felt by
the occupant in cases in which response generation is not possible
for questions regarding some or all functionality.
[0117] Since the scope of questions for which response generation
is not possible is confirmed at the point when the vehicle 12 is
started up, questions are not received in error, thus enabling a
sense of frustration felt by the user to be suppressed. Note that
the vehicle information reception timing does not necessarily have
to be when the vehicle 12 is started up.
[0118] Moreover, the confirmation section 53 of the agent server 16
of the present exemplary embodiment searches the vehicle-to-OM
association data 200 in which the associations between owner's
manuals and corresponding vehicles 12 are stored in order to
confirm the scope of questions for which response generation is not
possible. In the present exemplary embodiment, compiling a database
regarding the availability or unavailability of an owner's manual
for each vehicle 12 enables simpler management to block receipt of
questions for which response generation is not possible by the
onboard device 20.
[0119] The reception section 50 of the agent server 16 of the
present exemplary embodiment receives CAN information of the
vehicle 12 in addition to question information. The intent
inference section 38 performs intent inference processing as
inference processing employing both text information and CAN
information, and the acquisition section 52 acquires a response to
the question based on the inferred intent. The agent server 16 of
the present exemplary embodiment is capable of taking the state of
the vehicle 12 into account when inferring the intent of a
question, enabling the precision with which intent is inferred to
be improved.
[0120] Moreover, the agent server 16 of the present exemplary
embodiment infers intent using the trained model 240 generated in
advance by the intent inference section 38 performing machine
learning. The present exemplary embodiment enables training using
more information regarding the vehicles 12 and expressions, thereby
enabling the precision with which the intent of an occupant's
question is inferred to be improved. Note that in the data server
19, extra machine learning may be performed by acquiring CAN
information and response results to questions in order to generate
new trained models 240. Moreover, the trained models 240 of the
agent server 16 are updated, enabling the inference precision to be
further improved.
[0121] The agent server 16 of the present exemplary embodiment is
capable of acquiring CAN information of the vehicle 12 through the
external bus 20H that connects the plural ECUs 22 that control the
vehicle 12 together. In the present exemplary embodiment, utilizing
this vehicle control communication information enables simple
acquisition of the state of the vehicle 12 from the vehicle 12.
[0122] In the agent server 16 of the present exemplary embodiment,
as illustrated in FIG. 6, machine learning is performed based on
the state of the vehicle 12 during the predetermined duration.
Accordingly, in the present exemplary embodiment, setting the
predetermined duration to a duration in which, for example, the
occupant will have had a chance to notice a warning lamp or the
like enables a state of the vehicle 12 of which the occupant is
likely to be conscious to be taken into account when inferring the
intent.
[0123] In the manual provision system 10 according to the present
exemplary embodiment, the onboard device 20 installed to the
vehicle 12 is capable of providing a response to a question from
the occupant. The present exemplary embodiment is thus capable of
enhancing convenience of operation for the occupant of the vehicle
12.
[0124] In the present exemplary embodiment, the onboard device 20
is configured to gray out display of an input button 80 on the
monitor 28 as illustrated in FIG. 9, and block reception of
operation through the input button 80. The present exemplary
embodiment is thus capable of visually conveying to the occupant
when the agent is not available.
[0125] Note that although in the present exemplary embodiment
explanation has been given in which the corresponding input button
80 is grayed out when blocked from receiving operation, there is no
limitation thereto. For example, text reading "unavailable" or the
like may be displayed overlaid on the input button 80.
[0126] The onboard device 20 of the present exemplary embodiment
may also display text reading "preparing . . . ", "loading . . . "
or similar adjacent to or overlaid on the corresponding input
button 80 in cases in which an owner's manual associated with the
vehicle 12 is about to become available. In cases in which the
onboard device 20 has completed procurement of an owner's manual
associated with the vehicle 12, text such as "new" or "available
today!" may be displayed adjacent to or overlaid on the
corresponding input button 80. Moreover, the onboard device 20 may
change the color of the input button 80 over time, or gradually
reduce the grayed out effect, as the owner's manual associated with
the vehicle 12 transitions from being in the process of being
procured to procurement being completed. "Procurement" of the
owner's manual refers to adding the associated owner's manual to
the OM data 300 of the OM server 18 and adding information
associated with the owner's manual of the vehicle 12 to the
vehicle-to-OM association data 200 of the agent server 16.
Second Exemplary Embodiment
[0127] In the first exemplary embodiment, the intent inference
processing is executed based on text information and CAN
information, and a single intent label is acquired. By contrast, in
a second exemplary embodiment, plural intent labels are acquired
during the intent inference processing, and the CAN information is
consulted to execute intent identification processing to narrow
down to a single intent label. Namely, the intent inference
processing and the intent identification processing are executed as
the inference processing. Explanation follows regarding points that
differ from the first exemplary embodiment in the processing
performed in order to present a response to a question.
[0128] Explanation follows regarding processing performed in the
present exemplary embodiment from when the occupant of the vehicle
12 asks a question until presentation of a response, with reference
to the sequence charts of FIG. 13 and FIG. 14.
[0129] The processing from step S60 to step S63 in FIG. 13 matches
the processing of step S40 to step S43 in FIG. 10.
[0130] At step S64, the OMA interaction control section 36
identifies the OM item code associated with the vehicle
information. Namely, an owner's manual associated with the vehicle
identification number, vehicle type, grade, equipment, or the like
of the vehicle 12 is identified.
[0131] At step S65, the OMA interaction control section 36
identifies the intent inference engine ID associated with the OM
item code. Namely, the intent inference engine associated with the
owner's manual of the vehicle 12 is identified.
[0132] At step S66, the OMA interaction control section 36 provides
the text information and the intent inference engine ID acquired
from the HMI server 14 to the intent inference section 38.
[0133] At step S67, the intent inference section 38 executes the
intent inference processing, this being one part of the inference
processing. The intent inference section 38 thereby outputs intent
labels associated with the text information. For example, plural
intent labels associated with the inferred intent of the text
information "A meter lamp has come on, but what does it mean" are
output.
[0134] Moving on to FIG. 14, at step S68, the intent inference
section 38 provides the OMA interaction control section 36 with
plural intent labels that have confidence scores exceeding a
predetermined value. Note that in cases in which no intent labels
with a confidence score exceeding the predetermined value are
output, the intent inference section 38 provides the OMA
interaction control section 36 with no-label information to
indicate that no intent labels have been returned.
[0135] At step S69, the OMA interaction control section 36
determines whether or not any CAN information that should be
consulted is present. For example, suppose that as a result of the
intent inference processing, intent labels relating to warning
lamps relevant to a display 1, a display 2, and a display 10 are
acquired. In such cases, since CAN information relating to these
warning lamps can be consulted, CAN information that should be
consulted is determined to be present. The OMA interaction control
section 36 proceeds to step S70 in cases in which CAN information
that should be consulted is determined to be present. On the other
hand, the OMA interaction control section 36 proceeds to step S74
in cases in which CAN information that should be consulted is
determined not to be present.
[0136] At step S70, the OMA interaction control section 36 searches
for the CAN information. Namely, the OMA interaction control
section 36 attempts to acquire CAN information from the data server
19.
[0137] At step S71, the OMA interaction control section 36
transmits the vehicle information and the utterance start timestamp
to the data server 19.
[0138] At step S72, the data management section 39 of the data
server 19 transmits the CAN information or the no-information
notification to the agent server 16. Specific details of this step
match those of step S46 in FIG. 10.
[0139] At step S73, the OMA interaction control section 36, serving
as an identification section, executes the intent identification
processing, this being one element of the inference processing
using the CAN information. From the plural intent labels, the OMA
interaction control section 36 acquires a single intent label
associated with the CAN information. For example, in cases in which
CAN information indicating that the tire pressure warning lamp has
lit up has been acquired, an intent label relating to the tire
pressure warning system is acquired from out of the plural intent
labels. Namely, inference processing is executed by the intent
inference processing performed by the intent inference section 38
and by the intent identification processing performed by the OMA
interaction control section 36.
[0140] The subsequent processing from step S74 to step S78 matches
the processing of step S52 to step S56 in FIG. 11.
[0141] By performing the above processing, the manual provision
system 10 of the present exemplary embodiment is capable of
obtaining similar advantageous effects to those of the first
exemplary embodiment.
Third Exemplary Embodiment
[0142] In the first exemplary embodiment and the second exemplary
embodiment, the HMI server 14, the agent server 16, and the data
server 19 are configured by different servers 30. By contrast, in a
third exemplary embodiment, the HMI server 14 and the data server
19 are consolidated in the agent server 16, as illustrated in FIG.
15.
[0143] The manual provision system 10 of the present exemplary
embodiment is also capable of obtaining similar advantageous
effects to those of the first and second exemplary embodiments.
[0144] Remarks
[0145] In the exemplary embodiments described above, audio
information based on an utterance of an occupant configures the
input information of the HMI server 14. However, there is no
limitation thereto, and the input information may be configured by
operation information based on operation of the touch panel
configuring the monitor 28 by the occupant. In such cases, the
operation information is, for example, text information relating to
a text string input to the monitor 28 by the occupant.
[0146] In the third exemplary embodiment described above, the HMI
server 14 and the data server 19 included in the manual provision
system 10 are consolidated in the agent server 16. However, the OM
server 18 may also be consolidated. Alternatively, the servers 30
configuring some out of the HMI server 14, the agent server 16, the
OM server 18, and the data server 19 may be consolidated. Moreover,
in the agent server 16, the functionality of the OMA interaction
control section 36 and the intent inference section 38 may be
distributed between different servers 30.
[0147] The various processing executed by the CPUs 20A, 30A reading
software (a program) in the exemplary embodiments described above
may be executed by various types of processor other than the CPUs.
Such processors include programmable logic devices (PLDs) that
allow circuit configuration to be modified post-manufacture, such
as a field-programmable gate array (FPGA), and dedicated electric
circuits, these being processors including a circuit configuration
custom-designed to execute specific processing, such as an
application specific integrated circuit (ASIC). The processing
described above may be executed by any one of these various types
of processor, or by a combination of two or more of the same type
or different types of processor (such as plural FPGAs, or a
combination of a CPU and an FPGA). The hardware structure of these
various types of processors is more specifically an electric
circuit combining circuit elements such as semiconductor
elements.
[0148] The exemplary embodiments described above have described
implementations in which the program is in a format pre-stored
(installed) in a computer-readable non-transitory recording medium.
For example, the processing program 100 of each of the servers 30
is pre-stored in the corresponding storage 30D. However, there is
no limitation thereto, and the respective programs may be provided
in a format recorded on a non-transitory recording medium such as
compact disc read only memory (CD-ROM), digital versatile disc read
only memory (DVD-ROM), or universal serial bus (USB) memory.
Alternatively, the program may be provided in a format downloadable
from an external device through a network.
[0149] Instead of being executed by a single processor, the
processing of the exemplary embodiments described above may be
executed by plural processors working collaboratively. The
processing flows explained in the above exemplary embodiment are
merely examples, and superfluous steps may be omitted, new steps
may be added, or the processing sequences may be changed within a
range not departing from the spirit of the present disclosure.
[0150] An object of the present disclosure is to provide an agent
device, an agent system, and a non-transitory recording medium
capable of reducing a sense of frustration felt by a user in cases
in which an agent configured to infer the intent of a question
regarding vehicle functionality is unable to provide agent support
for some or all functionality.
[0151] A first aspect of the disclosure is an agent device that
includes: a memory; and a processor coupled to the memory. The
processor is configured to: receive, from an onboard device
installed in a vehicle, vehicle information relating to the vehicle
and question information corresponding to a question from a user,
based on the vehicle information, confirm a scope of questions for
which generation of a response is not possible, and instruct the
onboard device to block receipt of questions falling within the
scope of questions for which it has been confirmed that response
generation is not possible.
[0152] The agent device of the first aspect is capable of providing
the user with a response to the question from the user. The agent
device that receives the question information also receives the
vehicle information enabling the vehicle to be identified. Based on
the vehicle information, the agent device confirms the scope of
questions for which the response generation is not possible. Note
that cases in which "response generation is not possible" include
cases in which a manual stored with responses to questions has not
been compiled, and cases in which a manual is temporarily
unavailable due to an ongoing update. The agent device instructs
the onboard device to block receipt of questions falling within the
scope of questions for which the agent device has confirmed that
response generation is not possible. Accordingly, the agent device
is capable of reducing a sense of frustration felt by the user in
cases in which the response generation is not possible for
questions regarding some or all functionality.
[0153] A second aspect of the disclosure is the agent device of the
first aspect, wherein the processor is configured to search a
database storing state information indicating correspondence, to
respective vehicles, of manuals storing responses, and to confirm
the scope of questions for which response generation is not
possible based on presence or absence of a manual corresponding to
the vehicle information.
[0154] The agent device of the second aspect searches the database
in which the associations between the manuals and the vehicles are
stored in order to confirm the scope of questions for which
response generation is not possible. In this agent device,
compiling the database regarding the availability or unavailability
of a manual for each vehicle enables simpler management to block
receipt of questions for which the response generation is not
possible by the onboard device.
[0155] A third aspect of the disclosure is the agent device of the
first aspect, wherein the processor is configured to confirm the
scope of questions for which response generation is not possible at
a time of start-up of the vehicle.
[0156] In the agent device of the third aspect, since the scope of
questions for which the response generation is not possible is
confirmed at the point when the vehicle is started up, questions
are not received in error, thus enabling a sense of frustration
felt by the user to be reduced.
[0157] A fourth aspect of the disclosure is an agent system that
includes an agent device and an onboard device. The agent device
includes a memory and a processor coupled to the memory. The
processor is configured to receive, from an onboard device
installed in a vehicle, vehicle information relating to the vehicle
and question information corresponding to a question from a user,
based on the vehicle information, confirm a scope of questions for
which generation of a response is not possible, and instruct the
onboard device to block receipt of questions falling within the
scope of questions for which it has been confirmed that response
generation is not possible. The onboard device is configured to
control a display device provided to the vehicle so as to gray out
an input button relating to the question when instructed by the
agent device to block receipt.
[0158] In the agent system of the fourth aspect, the onboard device
installed in the vehicle is configured to gray out display of the
input button on the display device and block reception of operation
through the input button. This agent system is thus capable of
visually conveying to an occupant when an agent is not
available.
[0159] A fifth aspect of the disclosure is a non-transitory
recording medium that stores a program to cause a computer to
execute processing. The processing includes: receiving, from an
onboard device installed in a vehicle, vehicle information relating
to the vehicle on at a time of start-up of the vehicle, and
receiving question information corresponding to a question from a
user, based on the vehicle information, confirming a scope of
questions for which generation of a response is not possible; and
instructing the onboard device to block receipt of questions
falling within the scope of questions for which it has been
confirmed that response generation is not possible.
[0160] The program recorded in the non-transitory recording medium
of the fifth aspect is executable by a computer to perform
processing to provide the user with a response to the question from
the user. The computer executing this program receives the vehicle
information enabling the vehicle to be identified, and confirms the
scope of questions for which response generation is not possible
based on the vehicle information. Cases in which "response
generation is not possible" are as described previously. The
computer then instructs the onboard device to block receipt of
questions falling within the scope for which the response
generation has been confirmed as not possible. Accordingly, this
program is capable of reducing a sense of frustration felt by the
user in cases in which the response generation is not possible for
questions regarding some or all functionality.
[0161] A sixth aspect of the disclosure is the non-transitory
recording medium of the fifth aspect, wherein the processing
further comprises searching a database storing state information
indicating correspondence, to respective vehicles, of manuals
storing responses, and confirming the scope of questions for which
response generation is not possible based on presence or absence of
a manual corresponding to the vehicle information.
[0162] A seventh aspect of the disclosure is the non-transitory
recording medium of the fifth aspect, wherein the processing
further comprises confirming the scope of questions for which
response generation is not possible at a time of start-up of the
vehicle.
[0163] In the present disclosure is capable of reducing a sense of
frustration felt by a user in cases in which an agent configured to
infer the intent of a question regarding vehicle functionality is
unable to provide agent support for some or all functionality.
* * * * *